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AI Podcasts

December 16, 2025

Nvidia's Generative AI ecosystem supporting Japan's sovereign AI

Weights & Biases

AI
Key Takeaways:
  1. Ecosystem Dominance: NVIDIA's strategy extends beyond hardware; they are building an end-to-end ecosystem of software, open-source models, and direct support, making them indispensable for national AI initiatives.
  2. Builder Opportunity: Leverage NVIDIA's open-source Blueprints for agentic AI and Nemotron models for high-performance, customizable solutions. Prioritize local context in model training and data.
  3. Strategic Imperative: Sovereign AI is a growing global trend. Nations and companies that can build and control AI tailored to their specific cultural, linguistic, and regulatory environments will gain a significant advantage in the coming years.
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December 16, 2025

⚡️Jailbreaking AGI: Pliny the Liberator & John V on Red Teaming, BT6, and the Future of AI Security

Latent Space

AI
Key Takeaways:
  1. Strategic Shift: AI security must move beyond superficial guardrails to a full-stack, offensive red-teaming approach that accounts for the expanding attack surface of AI agents and their tool access.
  2. Builder/Investor Note: Builders should prioritize integrating offensive security early in development. Investors should be wary of "security theater" and favor solutions that embrace open-source collaboration and address the entire AI application stack.
  3. The "So What?": The accelerating pace of AI development means static security solutions will quickly become obsolete. Proactive, community-driven, and full-stack security research is essential for navigating the next 6-12 months of AI evolution.
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December 16, 2025

⚡️Jailbreaking AGI: Pliny the Liberator & John V on Red Teaming, BT6, and the Future of AI Security

Latent Space

AI
Key Takeaways:
  1. Strategic Implication: The "AI safety" narrative is shifting from content moderation to systemic security. Focus on hardening the entire AI ecosystem, not just restricting model outputs.
  2. Builder/Investor Note: Be wary of "AI security" products that claim to "secure the model" through guardrails. These are likely security theater. Invest in full-stack AI security solutions, red teaming services, and platforms that facilitate open-source adversarial research.
  3. The "So What?": The future of AI security is not about building higher walls around models, but about understanding and hardening the entire ecosystem in which they operate. Open collaboration and adversarial testing are the fastest paths to robust AI.
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December 16, 2025

Humanoid Robots: Hype vs Reality in 2026 | Rerun CEO

Weights & Biases

AI
Key Takeaways:
  1. Strategic Shift: The next frontier in robotics is less about pure algorithmic breakthroughs and more about building robust, scalable data infrastructure and full-stack product systems that can handle the messy physical world.
  2. Builder/Investor Note: Prioritize companies solving the "boring" but critical data and systems problems. Look for practical, "scrappy" companies deploying robots in specific industrial niches, rather than just those with flashy, general-purpose demos.
  3. The "So What?": The gap between impressive demos and deployable products will narrow over the next 6-12 months as data pipelines mature and product-focused companies gain traction. Expect to see more robust, self-correcting robots performing longer, more complex tasks in controlled environments.
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December 16, 2025

Why Physical AI Needs a new Data Set | Rerun CEO

Weights & Biases

AI
Key Takeaways:
  1. Data Infrastructure is the Next Bottleneck: The physical AI sector's growth hinges on specialized data tooling that can handle multimodal, multi-rate, episodic data, moving beyond traditional tabular models.
  2. Builders, Prioritize Robustness: Focus on building systems that handle real-world variability and simplify data pipelines. Leverage open-source tools and consider combining imitation and reinforcement learning.
  3. The "So What?": The next 6-12 months will see significant improvements in robot robustness and the ability to perform longer, more complex tasks. This progress will be driven by better data management, making the gap between lab demos and deployable products narrower.
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December 16, 2025

What We Learned Deploying AI within Bloomberg’s Engineering Organization – Lei Zhang, Bloomberg

AI Engineer

AI
Key Takeaways:
  1. Strategic Implication: AI fundamentally changes the economics of software development. Organizations must re-evaluate what constitutes "high-quality" engineering and adapt their processes.
  2. Builder/Investor Note: Prioritize platforms that provide guardrails and guidance for AI tool usage, focusing on deterministic verification and robust testing. Uncontrolled AI deployment risks technical debt.
  3. The "So What?": The next 6-12 months will see a bifurcation: companies that strategically integrate AI into their engineering culture and platforms will gain significant efficiency, while those that don't will struggle with quality and adoption.
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December 16, 2025

What We Learned Deploying AI within Bloomberg’s Engineering Organization – Lei Zhang, Bloomberg

AI Engineer

AI
Key Takeaways:
  1. Strategic Shift: AI's impact extends beyond simple productivity. The real opportunity lies in fundamentally changing the cost function of engineering, making previously expensive or undesirable tasks cheap and feasible.
  2. Platform Imperative: For large organizations, a "golden path" platform is not optional. It's how you manage complexity, ensure quality, and scale AI adoption safely and efficiently.
  3. Human-Centric Adaptation: Technology is only half the battle. Investing in cultural adaptation, community building, and leadership training is crucial for realizing AI's full potential.
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December 16, 2025

Finding The 1% of Stocks That Matter | Henry Ellenbogen Interview

Invest Like The Best

AI
Key Takeaways:
  1. Strategic Implication: The era of "free money" inflated the number of perceived compounders; a return to positive real rates demands a sharper focus on businesses demonstrating genuine financial discipline and competitive advantage.
  2. Builder/Investor Note: Seek out "Act 2" entrepreneurs and companies that can leverage AI to transform existing physical or IP-based advantages, not just create new AI products. Be prepared to buy more when market sentiment turns negative on strong businesses.
  3. The "So What?": The next 6-12 months will differentiate companies that merely adopt AI from those that strategically integrate it to build durable, uncatchable cost and distribution advantages.
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December 16, 2025

Finding The 1% of Stocks That Matter | Henry Ellenbogen Interview

Invest Like The Best

AI
Key Takeaways:
  1. Strategic Implication: The AI era will disproportionately reward existing businesses that deeply integrate AI to create unassailable cost structures, not just new AI-native ventures.
  2. Builder/Investor Note: Seek out resilient "Act II" leaders who embrace the "and" business—growth, innovation, and profitability—and are willing to navigate public market scrutiny for long-term alignment.
  3. The "So What?": Over the next 6-12 months, expect market volatility to create opportunities to invest in disciplined companies leveraging AI for fundamental operational shifts, rather than just hype.
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Crypto Podcasts

November 1, 2025

CFDs, Perps, and Tokenized Equities — The Next $10T Crypto Market? - The Chopping Block

Unchained

Crypto
Key Takeaways:
  1. Funding Rates Are a UX Bottleneck. For RWAs to succeed on-chain, derivative models must offer predictable costs. The volatile funding rates of crypto-native perps are a major barrier to mainstream adoption, pushing innovation toward CFD-like structures.
  2. The Airdrop Is Dead; Long Live the Curated ICO. Capital formation is shifting from broad, farmed airdrops to sophisticated, curated token sales. Projects now act like luxury brands, hand-picking investors to ensure long-term alignment, killing the "spray and pray" distribution model.
  3. Political Wins Can Backfire. The CZ pardon highlights the double-edged sword of crypto's political maneuvering. The perceived corruption and mainstream backlash create a massive reputational headache that undermines the industry’s push for legitimacy.
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October 31, 2025

Crypto Finally Goes Mainstream | Roundup

Bell Curve

Crypto
Key Takeaways:
  1. Banks Can't Ignore the Genie: Jamie Dimon's reversal and JPMorgan's new crypto services signal that institutional resistance is crumbling. The catalyst is the disruptive threat of stablecoins to core banking models.
  2. Consolidation is the Game: Mature sectors like exchanges and L1s are consolidating. The strategic play is to identify the dominant platforms (e.g., ETH, Solana, major exchanges) poised to compound value as moats widen.
  3. Regulation is the Kingmaker: Political moves, such as Trump pardoning CZ, are reshaping the competitive map. Access to the U.S. market will be a critical battleground, making regulatory strategy more important than ever.
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October 31, 2025

Crypto’s in a 20-Year Secular Bull Market | Weekly Roundup

Empire

Crypto
Key Takeaways:
  1. **The "Bloomberg for Crypto" is the Endgame.** The most valuable companies will provide institutional-grade data and software. Blockworks' pivot is a bet on this future, moving from a crowded news business to a high-growth data platform with clear product-market fit.
  2. **Tokenization is Now a Publicly Traded Thesis.** With Securitize’s IPO, investors can make a direct, public-market bet on the tokenization of real-world assets. It will likely be valued as a high-growth proxy for the entire sector.
  3. **Adoption is Bought, Not Begged.** Layer 1s are aggressively paying for partnerships with brands like Western Union. For investors, the question is whether these deals create a sustainable flywheel or just a temporary boost.
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October 30, 2025

Why I’m Short $1M of ETH.

Taiki Maeda

Crypto
Key Takeaways:
  1. The Q4 Pump is a Trap. The widespread belief in a year-end alt season has become a crowded exit strategy. When everyone plans to sell into the same pump, there’s no one left to buy.
  2. ETH's Fundamentals are Hollow. Ethereum's valuation is propped up by narratives, not reality. Weak on-chain activity and a value-accrual model that benefits apps over the base layer make its current price unsustainable.
  3. The Sellers Are Here. From VCs with token unlocks to treasury companies turning into paper hands, identifiable sellers now outweigh the speculative buyers, signaling the cycle has turned.
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October 30, 2025

Hivemind: Crypto's Leverage Hangover, Hyperliquid's Resurgance & What's Next for Markets?

Empire

Crypto
Key Takeaways:
  1. Survive, Then Thrive. After massive liquidations, the strongest assets and narratives (e.g., privacy plays like Zcash) recover first. Focus capital on names showing relative strength post-wipeout, as they are the first to capture returning liquidity.
  2. Revenue is the New Narrative. The game has changed. The market now demands clear revenue streams and legal structures that align token holders with protocol success. Valueless governance tokens are out; tokens tied to real business operations are in.
  3. On-Chain TradFi is Here. Platforms like Hyperliquid are successfully bringing assets like the NASDAQ on-chain, proving crypto-native demand for traditional markets. This represents a major new frontier for DeFi protocols looking to capture volume.
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October 29, 2025

Deficits Are Forcing the Fed Back Into Expansion | Lyn Alden

Forward Guidance

Crypto
Key Takeaways:
  1. **Fiscal is the new Fed.** Government spending, not central bank policy, is the dominant force in the economy. Stop looking for a traditional recession; the deficit is the stimulus that won’t quit.
  2. **The Fed is re-opening the liquidity spigot.** The era of Quantitative Tightening is over. A gradual but persistent expansion of the Fed's balance sheet is coming, which will provide a tailwind for assets.
  3. **Own scarce assets.** The long-term debasement of fiat currency is the default path. Alden remains constructive on Bitcoin, viewing its current phase as a prelude to a significant move higher in the coming years.
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